Advancing from statistical associations of complex traits with genetic markers to
understanding the functional genetic variants that influence traits is often a complex process …

During the past decade, genome-wide association studies (GWAS) have been used to
successfully identify tens of thousands of genetic variants associated with complex traits and …

Understanding kidney disease relies on defining the complexity of cell types and states, their
associated molecular profiles and interactions within tissue neighbourhoods. Here we …

Here we conducted a large-scale genetic association analysis of educational attainment in a
sample of approximately 1.1 million individuals and identify 1,271 independent genome …

In recent work, Wang et al introduced the “Sum of Single Effects”(SuSiE) model, and showed
that it provides a simple and efficient approach to fine-mapping genetic variants from …

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder
with a major genetic component. Here, we present a genome-wide association study meta …

We introduce a simple new approach to variable selection in linear regression, with a
particular focus on quantifying uncertainty in which variables should be selected. The …

Common variant genome-wide association studies (GWASs) have, to date, identified> 24
risk loci for Parkinson's disease (PD). To discover additional loci, we carried out a GWAS …

The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding
regions of the genome. One possible hypothesis is that these GWAS risk loci alter the …

Fine-mapping is commonly used to identify putative causal variants at genome-wide
significant loci. Here we propose a Bayesian model for fine-mapping that has several …